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Laboratory of Computer and Information Science / Neural Networks Research Centre CIS Lab Helsinki University of Technology

Assignment: Independent component analysis (ICA)

You must return a written report in which you provide justified answers to the questions in the assignment. Explain what you have done and why. The complete, sufficiently commented source code should be included as an appendix in the report. The report can be returned by email in PDF or PostScript format to the assistant.

This computer assignment starts with getting acquainted in practice to the popular Matlab software package FastICA. It has been developed by A. Hyvärinen et al. in HUT, Lab. of Computer and Information Science, for estimating the basic linear ICA and BSS model. The main goal of this computer assignment is to apply FastICA to the extraction of features from image data consisting of natural scenes using ICA.

Material

Data and Codes (tar.gz, zip)

Useful Matlab commands

help
plot
rand, randn
reshape
hist
mean
conv2
imagesc

Useful FastICA options

Option:                Values:
g                      'pow3', 'tanh', 'gauss', 'skew'
approach               'symm', 'defl'
lastEig
stabilization

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